Why are output tokens more expensive than input tokens?

Generating output tokens requires iterative autoregressive decoding on GPU clusters, which is computationally heavier than parallel prefilling of input tokens.

Updated: August 2026 • Verified v1.2

LLM Token & API Cost Calculator

AI & PromptingEssential

Local Browser Execution: Your input is processed locally in your browser and is not sent to UTL servers.

Single Cost = (Input Tokens / 1M * Input Rate) + (Output Tokens / 1M * Output Rate)

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Understanding Your Results

Calculates exact cost per single inference request, daily burn, and 30-day monthly projected cost based on token volumes and request frequency.

Practical Guidance & Next Steps

Paste prompt drafts into the optional estimator box to get instant approximate token counts before deploying production prompts.

What is this?

An interactive AI pricing calculator that translates prompt and completion tokens into exact dollar costs across all major frontier LLM APIs.

How does it work?

1. Select your AI model (GPT-4o, Claude 3.5 Sonnet, Gemini 1.5, DeepSeek, or Custom). 2. Enter your estimated input and output tokens (or paste prompt text). 3. Set daily request volume to see instant per-call, daily, and monthly costs.

Why use it?

Prevents API billing surprises and helps engineering teams budget LLM infrastructure accurately.

Technical Scope & Calculation Limitations

Token counts are heuristic approximations (~4 characters/token for English). Actual tokenization varies slightly by provider BPE tokenizers.

Frequently Asked Questions

In standard English text, 1,000 tokens corresponds to approximately 750 words (or about 4,000 characters).

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